class_docstr: Base class for neural network layers. Subclass must implement `forward` function.
docstr: Get parameters for training along with the learning rate.
  
  Args:
      weight_decay: weight decay
      no_decay_bn_filter_bias: Do not decay BN and biases. Defaults to False.
  
  Returns:
       Returns a tuple of length 2. The first entry is a list of dictionary with three keys
       (params, weight_decay, param_names). The second entry is a list of floats containing
       learning rate for each parameter.
  
  Note:
      Learning rate multiplier is set to 1.0 here as it is handled inside the Central Model.
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code: def get_trainable_parameters(
      self,
      weight_decay: Optional[float] = 0.0,
      no_decay_bn_filter_bias: Optional[bool] = False,
      *args,
      **kwargs,
  ) -> Tuple[List[Dict], List[float]]:
      """
      Get parameters for training along with the learning rate.
  
      Args:
          weight_decay: weight decay
          no_decay_bn_filter_bias: Do not decay BN and biases. Defaults to False.
  
      Returns:
           Returns a tuple of length 2. The first entry is a list of dictionary with three keys
           (params, weight_decay, param_names). The second entry is a list of floats containing
           learning rate for each parameter.
  
      Note:
          Learning rate multiplier is set to 1.0 here as it is handled inside the Central Model.
      """
      param_list = parameter_list(
          named_parameters=self.named_parameters,
          weight_decay=weight_decay,
          no_decay_bn_filter_bias=no_decay_bn_filter_bias,
          *args,
          **kwargs,
      )
      return param_list, [1.0] * len(param_list)
  
file_path: ml-cvnets/cvnets/layers/base_layer.py
imports: import argparse
  from typing import Any, Dict, List, Optional, Tuple
  from torch import nn
  from cvnets.misc.common import parameter_list
label_desc: Use image node_id 3 for calling the BaseLayer obj's underlying member method code with example usage: obj.get_trainable_parameters(weight_decay, no_decay_bn_filter_bias) and returns: param_list,  unknown